基于自适应的非线性几何变换的量子算法验证

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper investigates the application of a novel quantum algorithm validation framework, predicated on adaptive non-linear geometric transformations, to assess the quantum efficiency and accuracy of matrix transformations. Traditional quantum algorithm validation often relies on static approaches, struggling with the complexities of non-linear geometric variations. This work proposes a framework leveraging quantum properties to provide a more precise and robust validation mechanism for quantum algorithms. The core mechanism centers around dynamically adjusting geometric parameters to precisely characterize the algorithm's behavior, ultimately offering a superior verification process. This paper details the framework's design, explores its application to a specific matrix transformation, and highlights the potential benefits of this approach. The investigation demonstrates a significant improvement in quantum algorithm verification compared to traditional methods.

DOI: 10.5281/zenodo.22499327

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